Reservoir operation optimization (ROO) is a complicated dynamically constrained nonlinear problem that is important in the context of reservoir system operation. In this study, improved adaptive particleswarm optimiz...
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Reservoir operation optimization (ROO) is a complicated dynamically constrained nonlinear problem that is important in the context of reservoir system operation. In this study, improved adaptive particleswarmoptimization (IAPSO) is proposed to solve the problem, which involves many conflicting objectives and constraints. The proposed algorithm takes particleswarmoptimization (PSO) as the main evolution method. To overcome the premature convergence of PSO, adjusting dynamically the two sensitive parameters of PSO guides the evolution direction of each particle in the evolution process. In the IAPSO method, an adaptive dynamic parameter control mechanism is applied to determine parameter settings. Moreover, a new strategy is proposed to handle the reservoir output constraint of ROO problem. Finally, the feasibility and effectiveness of the proposed IAPSO algorithm are validated by the Three Gorges Project (TGP) with 42.23 bkW power generation and XiLuoDo Project (XLDP) with 30.10 bkW. Compared with other methods, the IAPSO provides a better operational result with greater effectiveness and robustness, and appears to be better in terms of power generation benefit and convergence performance. Meanwhile, the optimal results could meet output constraint at each interval. (C) 2014 Elsevier B.V. All rights reserved.
Epilepsy is a disease caused by abnormal discharges in the central nervous system. Automatic detection and accurate identification of epileptic seizures based on electroencephalography (EEG) are significant in the cli...
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Epilepsy is a disease caused by abnormal discharges in the central nervous system. Automatic detection and accurate identification of epileptic seizures based on electroencephalography (EEG) are significant in the clinical diagnosis and treatment of epilepsy. In this paper, we first decompose the patient's EEG signal into multiple intrinsic modal functions (IMFs) using empirical modal decomposition, then compute the mean, standard deviation, fluctuation index, and sample entropy of IMF1, and finally classify them using a fusion algorithm of support vector machine and K-nearest neighbor optimized by particleswarmalgorithm. The results of validation using the epileptic EEG data set from Bonn University show that the auto-detection and fast recognition method proposed in this paper can achieve a high seizure accuracy recognition rate (>= 95%) with only a small number of training samples, which has a good clinical application value.
The heat transfer mechanism for radiation is directly related to the emission of photons and electromagnetic waves. Depending on the participation of the medium, the radiation can be classified into two forms: surface...
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The heat transfer mechanism for radiation is directly related to the emission of photons and electromagnetic waves. Depending on the participation of the medium, the radiation can be classified into two forms: surface and gas radiation. In the present study, unknown radiation properties were estimated using an inverse boundary analysis of surface radiation in an axisymmetric cylindrical enclosure. For efficiency, a repulsive particleswarmoptimization (RPSO) algorithm, which is a relatively recent heuristic search method, was used as inverse solver. By comparing the convergence rates and accuracies with the results of a genetic algorithm (GA), the performances of the proposed RPSO algorithm as an inverse solver was verified when applied to the inverse analysis of the surface radiation problem.
In this paper, a communication strategy for hybrid particleswarmoptimization (PSO) with Bat algorithm (BA) is proposed for solving numerical optimization problems. In this work, several worst individuals of particle...
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ISBN:
(纸本)9783319122854
In this paper, a communication strategy for hybrid particleswarmoptimization (PSO) with Bat algorithm (BA) is proposed for solving numerical optimization problems. In this work, several worst individuals of particles in PSO will be replaced with the best individuals in BA after running some fixed iterations, and on the contrary, the poorer individuals of BA will be replaced with the finest particles of PSO. The communicating strategy provides the information flow for the particles in PSO to communicate with the bats in BA. Six benchmark functions are used to test the behavior of the convergence, the accuracy, and the speed of the approached method. The results show that the proposed scheme increases the convergence and accuracy more than BA and PSO up to 3% and 47% respectively.
In the Tokamak discharge experiment, obtaining the largest possible null field region is a necessary condition for the smooth breakdown of the plasma, and adjusting the poloidal field coil current is key to achieving ...
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In the Tokamak discharge experiment, obtaining the largest possible null field region is a necessary condition for the smooth breakdown of the plasma, and adjusting the poloidal field coil current is key to achieving a better null field region. This paper, based on the Sino-Thai Tokamak cooperation project Thailand Tokamak-1 (TT-1) device, employs an exponentially decreasing particleswarmoptimization (PSO) algorithm to optimize the poloidal field coil current to create the desired null field region in the vacuum chamber area. First, a calculation model for the mutual inductance coefficient and the null field region is established according to the characteristics and magnetic structure of the TT-1 device, enabling the calculation of the null field region. Then, an optimization model for the poloidal field coil current is established, aiming to create a sufficiently large null field region (less than 10 Gauss) to facilitate breakdown. The optimization is carried out using both a typical linearly decreasing PSO algorithm and an improved PSO algorithm to determine the optimal poloidal field coil current. Compared to the unmodified PSO algorithm, the improved PSO algorithm reduces the root mean square error by 31.80%. The results show that the improved PSO algorithm is more suitable for the optimization of the poloidal field coil, has stronger optimization capabilities, and can effectively create the desired null field region, providing an important reference for the smooth breakdown of plasma in the TT-1 device.
In this paper, through the analysis of the characteristics of particle swarm optimization algorithm, combined with the specific circumstances of Bayesian network structure learning, proposed to based on improved parti...
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ISBN:
(纸本)9783037859926
In this paper, through the analysis of the characteristics of particle swarm optimization algorithm, combined with the specific circumstances of Bayesian network structure learning, proposed to based on improved particleswarmalgorithm. The algorithm uses the BIC measure function as a standard Bayesian network, while preserving the optimal particle case, the possibility of a mutation operation is added to decrease the algorithm into a local optimum. Through a typical Asia network, show that the algorithm is feasible, and other related algorithm is better than the experiment, the effectiveness of the algorithm. In this paper, the algorithm is verified from two aspects of theory and experiments, the results show that the algorithm is feasible.
In fluid mechanics, how to solve power-law fluids in ordinary differential equations is always a concerned and difficult problem. we use generally a shooting method to tackle the boundary-layer problems under a suctio...
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ISBN:
(纸本)9783038350095
In fluid mechanics, how to solve power-law fluids in ordinary differential equations is always a concerned and difficult problem. we use generally a shooting method to tackle the boundary-layer problems under a suction/injection as well as a reverse flow boundary conditions. A improved particle swarm optimization algorithm (ISPO) is proposed for solving the parameter estimation problems of the multiple solutions in fluid mechanics. This algorithm has improved greatly in precision and the success rate. In this paper, multiple solutions can be found through changing accuracy and search coverage and multi-iterations of computer. Parameter estimation problems of the multiple solutions of ordinary differential equations are calculated, and the result has great accuracy and this method is practical.
Hyperspectral images have been widely used in earth observation. However, there are some problems such as huge amount of data and high correlation between bands. An application of particle swarm optimization algorithm...
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ISBN:
(纸本)9783038350156
Hyperspectral images have been widely used in earth observation. However, there are some problems such as huge amount of data and high correlation between bands. An application of particle swarm optimization algorithm based on B distance was proposed to band selection of hyperspectral images. First of all, bands are grouping by the correlation coefficient of the band and adjacent bands. B distance was used as separability criterion between classes and the fitness function comes into being. Finally, the classification results illustrate that the total classification accuracy of the proposed method is higher than the traditional method.
In this paper, parameter of ADRC for spacecraft attitude maneuvering is optimizated. Nonlinear dynamics model of spacecraft attitude describes attitude motion. particle swarm optimization algorithm is used for paramet...
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ISBN:
(纸本)9781479949557
In this paper, parameter of ADRC for spacecraft attitude maneuvering is optimizated. Nonlinear dynamics model of spacecraft attitude describes attitude motion. particle swarm optimization algorithm is used for parameter optimization of ADRC. The controller index which describes attitude adjustment capacity of three axes is designed. The influence of controller parameter is quantifiable on the control performance. The selection of parameter based on traditonal experience is avoided. Simulation results show that: the particle swarm optimization algorithm for system updates through the position and velocity. The system can quickly converge to the global optimal solution, and the parameter of ADRC is optimized.
The thickness of multi-layer absorbing material is optimized to obtain lower electromagnetic reflection coefficient by using particleswarmoptimization (PSO) algorithm in this paper. Two examples are employed to vali...
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ISBN:
(纸本)9783037859087
The thickness of multi-layer absorbing material is optimized to obtain lower electromagnetic reflection coefficient by using particleswarmoptimization (PSO) algorithm in this paper. Two examples are employed to validate the excellent performance of PSO. The results show that the reflection coefficient of absorbing material is less than-20 dB over the bandwidth of 2GHz similar to 18GHz, less than -25 dB over the narrowband of 9 GHz similar to 11GHz, less than-30 dB during the bandwidth of 9.5 GHz similar to 10.5 GHz. It also shows that the minimum value approaches to -48 dB in a certain range.
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